The Biased Algorithm: Evidence of Disparate Impact on Hispanics

Abstract

Automated risk assessment is all the rage in the criminal justice system. Proponents view risk assessment as an objective way to reduce mass incarceration without sacrificing public safety. Officials thus are becoming heavily invested in risk assessment tools—with their reliance upon big data and algorithmic processing—to inform decisions on managing offenders according to their risk profiles. This Article intends to partly remedy this gap in interest by reporting on an empirical study about risk assessment with Hispanics at the center. The study uses a large dataset of pretrial defendants who were scored on a widely-used algorithmic risk assessment tool soon after their arrests. The report proceeds as follows. Section II briefly reviews the rise in algorithmic risk assessment in criminal justice generally, and then in pretrial contexts more specifically. The discussion summarizes the ProPublica findings regarding the risk tool COMPAS after it analyzed COMPAS scores comparing Blacks and Whites.

Melissa Hamilton

Dr Melissa Hamilton is a member of the Hub and a Professor at the School of Law.